At the Karolinska Institute’s center for cervical cancer prevention, sequencing machines have generated 800+ TBs of next-generation sequencing data, requiring both low-cost storage and secure large-scale processing by researchers.
They use large amounts of data from omics analyses to gain new insights into the biology of viruses. For an individual research group or even a university alone, these large volumes would be very difficult or even impossible to process. Providing standardized solutions at this scale requires international collaboration.
The organisation utilizes large-scale processing on Apache Spark and deep learning on TensorFlow to analyze these scale sensitive datasets to identify novel viruses, perform large cohort studies, and identify genetic mutations causing diseases. However:
Karolinska Institute deployed Hopsworks to manage genomic data and conduct secure research studies. Hopsworks was built around projects, providing a GDPR-compliant environment that enables secure collaboration between researchers on medical studies within a shared cluster.
Hopsworks is optimized for commodity hardware and runs on any data center. Clusters can be easily expanded by adding capacity, when needed enabling a low cost solution for up to PBs of data. Similarly, Hopsworks supports commodity or enterprise GPUs that can be used for deep learning.
Hopsworks’ user-friendly web interface enables researchers to run, manage and access data and programs without software administration knowledge and skills.
Hopsworks Multi-tenant Security Model helped Karolinska Institute to provide collaboration between researchers to manage, share and use genomic data without compromising data security and GDPR.
90% Cost Reduction
Costs savings associated with storing large volumes of data, as well as compute resources (CPU) and Graphical Processing Units (GPUs) to process this data.
Integrated Data Science Platform
Easy collaboration between researchers when managing, sharing, and processing genomic data.
Faster Data Processing
Massively parallel data processing pipeline for massive genomic datasets.
Karolinska Institute is one of the world’s foremost medical universities. KI accounts for the single largest share of all academic medical research conducted in Sweden and offers the country’s broadest range of education in medicine.
The Swedish Public Employment Service is a Swedish government agency organized under the Ministry of Employment mainly responsible for the public employment service in Sweden and the implementation of labour market policies.
HEAP provides an open access, technical research platform to assess the impact of the exposome on human health. It contains high-quality exposome data from five different cohort studies, and will be scalable to any research setting.